1. Technical Field
The present invention relates to improvements in network design and in particular to improved methods and systems for capacity calculation in a shared transmission medium network. Still more particularly, the present invention relates to a method and system for service capacity calculation for multimedia services under aggregate traffic conditions in a network having identifiable busy periods.
2. Description of the Related Art
No where has the explosion of modern technology been more evident than in the field of communication. The number and type of communication services has been rapidly expanding, including so-called "multimedia" services such as video teleconferencing, video/movies on demand and the like.
The intermixing of these multimedia services with traditional data and voice communications within a shared transmission medium has presented various design problems. For example, consider a system which receives packetized telecommunication traffic from n multimedia services which are queued either in one central queue or in multiple distributed queues wherein one queue is associated with each service. Thus, if more than n subscribers to the services are utilizing the network at any given time, the received packets which are not processed by the system are queued. During heavy use periods, as the number of users increase, and these queues become quite large, certain packets may be discarded based upon a priority scheme and delay will increase and quality of service will suffer.
Consequently, those skilled in the art will appreciate that one design requirement for a viable multimedia network requires that a limit exits for the number of users simultaneously connected to the network so that customer expectations and network efficiency will not suffer.
One common technique utilized in the past to satisfy customer expectations is to ensure that the quality of service parameter values for the multimedia services are not exceeded. In view of the fact that a modern network may include multiple diverse multimedia services having variable quality of service values, this has been very difficult to accomplish.
In the past, attempts at statistically modeling aggregate traffic which originates from homogenous services with similar traffic types and similar characteristics have been proposed. For example, the Poisson Process is widely utilized to model aggregate traffic from voice sources. Similarly, the discreet Auto Regressive Process has been utilized to model aggregate traffic from video-teleconferencing sources. A Markov Modulated Poisson Process is often utilized to model aggregate traffic from data sources. These techniques typically require complex mathematical expressions which are not explicit and which require time-consuming numerical methods to solve.
Service capacity is defined as the maximum number of users that the system can support so that the values of the quality of service parameters are not violated. Thus, while the simultaneous capacity of a multimedia network, i.e. the maximum number of users or subscribers which can simultaneously access individual services within that network so that the values of the quality of service parameters are not violated, can be determined by various techniques, these techniques result in an underestimate of the total service capacity of the network since maximum simultaneous capacity will not be attained constantly. One difficulty utilizing the prior art techniques for extending simultaneous capacity to service capacity is the problem that there may be several busy periods within each day and that there can be several busy days within each week. Thus, techniques for calculating simultaneous capacity for multimedia service within a network have not been generally successful in the calculation of service capacity for a network.
Thus, those skilled in the art will appreciate that a method and system for accurately and efficiently calculating total service capacity of multimedia services under aggregate traffic conditions would greatly enhance the efficiency of network design and the level of customer satisfaction.